[R] Clarification on Simulation and Iteration

[Michael Dewey]

I am not sure how you are doing this but there is a package on CRAN 
which implements the Copas model (metasens). I am not sure whether that 
would help in your modelling.

On 01/08/2015 02:36, Christopher Kelvin via R-help wrote:
> Dear All,
> I am performing some simulations for a new model. I run about 10,000 iterations with a sample of 50 datasets and this returns one set of 50 simulated data.
>
> Now, what I need to obtain is 10 sets of the 50 simulated data out of the 10,000 iterations and not just only 1 set.  The model is the Copas selection model for publication bias in Mete-analysis. Any one who knows this model has any suggestion for the improvement of my code is most welcome.
>
> Below is my code.
>
>
> Kind regards
>
>
> Chris Guure
> University of Ghana
>
>
>
>
> install.packages("msm")
> library(msm)
>
>
> rho1=-0.3; tua=0.020; n=50; d=-0.2; rr=10000; a=-1.3; b=0.06
> si<-rtnorm(n, mean=0, sd=1, lower=0, upper=0.2)# I used this to generate standard errors for each study
> set.seed(21111)   ## I have stored the data and the output in this seed
>
> for( i in 1:rr){
>
> mu<-rnorm(n,d,tua^2)              # prob. of each effect estimate
> rho<-si*rho1/sqrt(tua^2 + si^2) # estimate of the correlation coefficient
> mu0<- a + b/si       # mean of the truncated normal model (Copas selection model)
> y1<-rnorm(mu,si^2)            # observed effects zise
> z<-rnorm(mu0,1)               # selection model
> rho2<-cor(y1, z)
>
> select<-pnorm((mu0 + rho*(y1-mu)/sqrt(tua^2 + si^2))/sqrt(1-rho^2))
> probselect<-ifelse(select<z, y1, NA)# the prob that the study is selected
>
> probselect
> data<-data.frame(probselect,si)    # this contains both include and exclude data
> data
> data1<-data[complete.cases(data),] # Contains only the included data for analysis
> data1
>
>
> }
>
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-- 
Michael
http://www.dewey.myzen.co.uk/home.html